added support of CCOEFF_NORMED for multichannel images (8U) into gpu::matchTemplate
This commit is contained in:
Alexey Spizhevoy
parent
640af6623c
commit
343c33d73e
@ -600,7 +600,7 @@ void matchTemplatePrepared_CCOFF_NORMED_8U(
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float weight = 1.f / (w * h);
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float templ_sum_scale = templ_sum * weight;
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float templ_sqsum_scale = templ_sqsum - templ_sum * templ_sum * weight;
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float templ_sqsum_scale = templ_sqsum - weight * templ_sum * templ_sum;
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matchTemplatePreparedKernel_CCOFF_NORMED_8U<<<grid, threads>>>(
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w, h, weight, templ_sum_scale, templ_sqsum_scale,
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image_sum, image_sqsum, result);
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@ -608,6 +608,231 @@ void matchTemplatePrepared_CCOFF_NORMED_8U(
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}
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__global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8UC2(
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int w, int h, float weight,
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float templ_sum_scale_r, float templ_sum_scale_g,
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float templ_sqsum_scale,
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const PtrStep_<unsigned int> image_sum_r, const PtrStep_<unsigned long long> image_sqsum_r,
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const PtrStep_<unsigned int> image_sum_g, const PtrStep_<unsigned long long> image_sqsum_g,
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DevMem2Df result)
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{
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const int x = blockIdx.x * blockDim.x + threadIdx.x;
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const int y = blockIdx.y * blockDim.y + threadIdx.y;
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if (x < result.cols && y < result.rows)
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{
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float image_sum_r_ = (float)(
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(image_sum_r.ptr(y + h)[x + w] - image_sum_r.ptr(y)[x + w]) -
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(image_sum_r.ptr(y + h)[x] - image_sum_r.ptr(y)[x]));
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float image_sqsum_r_ = (float)(
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(image_sqsum_r.ptr(y + h)[x + w] - image_sqsum_r.ptr(y)[x + w]) -
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(image_sqsum_r.ptr(y + h)[x] - image_sqsum_r.ptr(y)[x]));
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float image_sum_g_ = (float)(
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(image_sum_g.ptr(y + h)[x + w] - image_sum_g.ptr(y)[x + w]) -
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(image_sum_g.ptr(y + h)[x] - image_sum_g.ptr(y)[x]));
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float image_sqsum_g_ = (float)(
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(image_sqsum_g.ptr(y + h)[x + w] - image_sqsum_g.ptr(y)[x + w]) -
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(image_sqsum_g.ptr(y + h)[x] - image_sqsum_g.ptr(y)[x]));
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float ccorr = result.ptr(y)[x];
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float rdenom = rsqrtf(templ_sqsum_scale * (image_sqsum_r_ - weight * image_sum_r_ * image_sum_r_
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+ image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_));
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result.ptr(y)[x] = min(1.f, (ccorr - image_sum_r_ * templ_sum_scale_r
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- image_sum_g_ * templ_sum_scale_g) * rdenom);
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}
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}
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void matchTemplatePrepared_CCOFF_NORMED_8UC2(
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int w, int h,
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const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
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const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
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unsigned int templ_sum_r, unsigned int templ_sqsum_r,
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unsigned int templ_sum_g, unsigned int templ_sqsum_g,
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DevMem2Df result)
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{
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dim3 threads(32, 8);
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dim3 grid(divUp(result.cols, threads.x), divUp(result.rows, threads.y));
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float weight = 1.f / (w * h);
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float templ_sum_scale_r = templ_sum_r * weight;
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float templ_sum_scale_g = templ_sum_g * weight;
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float templ_sqsum_scale = templ_sqsum_r - weight * templ_sum_r * templ_sum_r
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+ templ_sqsum_g - weight * templ_sum_g * templ_sum_g;
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matchTemplatePreparedKernel_CCOFF_NORMED_8UC2<<<grid, threads>>>(
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w, h, weight,
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templ_sum_scale_r, templ_sum_scale_g,
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templ_sqsum_scale,
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image_sum_r, image_sqsum_r,
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image_sum_g, image_sqsum_g,
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result);
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cudaSafeCall(cudaThreadSynchronize());
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}
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__global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8UC3(
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int w, int h, float weight,
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float templ_sum_scale_r, float templ_sum_scale_g, float templ_sum_scale_b,
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float templ_sqsum_scale,
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const PtrStep_<unsigned int> image_sum_r, const PtrStep_<unsigned long long> image_sqsum_r,
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const PtrStep_<unsigned int> image_sum_g, const PtrStep_<unsigned long long> image_sqsum_g,
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const PtrStep_<unsigned int> image_sum_b, const PtrStep_<unsigned long long> image_sqsum_b,
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DevMem2Df result)
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{
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const int x = blockIdx.x * blockDim.x + threadIdx.x;
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const int y = blockIdx.y * blockDim.y + threadIdx.y;
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if (x < result.cols && y < result.rows)
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{
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float image_sum_r_ = (float)(
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(image_sum_r.ptr(y + h)[x + w] - image_sum_r.ptr(y)[x + w]) -
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(image_sum_r.ptr(y + h)[x] - image_sum_r.ptr(y)[x]));
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float image_sqsum_r_ = (float)(
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(image_sqsum_r.ptr(y + h)[x + w] - image_sqsum_r.ptr(y)[x + w]) -
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(image_sqsum_r.ptr(y + h)[x] - image_sqsum_r.ptr(y)[x]));
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float image_sum_g_ = (float)(
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(image_sum_g.ptr(y + h)[x + w] - image_sum_g.ptr(y)[x + w]) -
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(image_sum_g.ptr(y + h)[x] - image_sum_g.ptr(y)[x]));
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float image_sqsum_g_ = (float)(
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(image_sqsum_g.ptr(y + h)[x + w] - image_sqsum_g.ptr(y)[x + w]) -
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(image_sqsum_g.ptr(y + h)[x] - image_sqsum_g.ptr(y)[x]));
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float image_sum_b_ = (float)(
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(image_sum_b.ptr(y + h)[x + w] - image_sum_b.ptr(y)[x + w]) -
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(image_sum_b.ptr(y + h)[x] - image_sum_b.ptr(y)[x]));
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float image_sqsum_b_ = (float)(
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(image_sqsum_b.ptr(y + h)[x + w] - image_sqsum_b.ptr(y)[x + w]) -
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(image_sqsum_b.ptr(y + h)[x] - image_sqsum_b.ptr(y)[x]));
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float ccorr = result.ptr(y)[x];
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float rdenom = rsqrtf(templ_sqsum_scale * (image_sqsum_r_ - weight * image_sum_r_ * image_sum_r_
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+ image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_
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+ image_sqsum_b_ - weight * image_sum_b_ * image_sum_b_));
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result.ptr(y)[x] = min(1.f, (ccorr - image_sum_r_ * templ_sum_scale_r
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- image_sum_g_ * templ_sum_scale_g
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- image_sum_b_ * templ_sum_scale_b) * rdenom);
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}
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}
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void matchTemplatePrepared_CCOFF_NORMED_8UC3(
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int w, int h,
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const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
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const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
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const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
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unsigned int templ_sum_r, unsigned int templ_sqsum_r,
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unsigned int templ_sum_g, unsigned int templ_sqsum_g,
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unsigned int templ_sum_b, unsigned int templ_sqsum_b,
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DevMem2Df result)
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{
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dim3 threads(32, 8);
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dim3 grid(divUp(result.cols, threads.x), divUp(result.rows, threads.y));
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float weight = 1.f / (w * h);
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float templ_sum_scale_r = templ_sum_r * weight;
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float templ_sum_scale_g = templ_sum_g * weight;
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float templ_sum_scale_b = templ_sum_b * weight;
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float templ_sqsum_scale = templ_sqsum_r - weight * templ_sum_r * templ_sum_r
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+ templ_sqsum_g - weight * templ_sum_g * templ_sum_g
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+ templ_sqsum_b - weight * templ_sum_b * templ_sum_b;
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matchTemplatePreparedKernel_CCOFF_NORMED_8UC3<<<grid, threads>>>(
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w, h, weight,
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templ_sum_scale_r, templ_sum_scale_g, templ_sum_scale_b,
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templ_sqsum_scale,
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image_sum_r, image_sqsum_r,
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image_sum_g, image_sqsum_g,
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image_sum_b, image_sqsum_b,
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result);
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cudaSafeCall(cudaThreadSynchronize());
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}
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__global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8UC4(
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int w, int h, float weight,
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float templ_sum_scale_r, float templ_sum_scale_g, float templ_sum_scale_b,
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float templ_sum_scale_a, float templ_sqsum_scale,
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const PtrStep_<unsigned int> image_sum_r, const PtrStep_<unsigned long long> image_sqsum_r,
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const PtrStep_<unsigned int> image_sum_g, const PtrStep_<unsigned long long> image_sqsum_g,
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const PtrStep_<unsigned int> image_sum_b, const PtrStep_<unsigned long long> image_sqsum_b,
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const PtrStep_<unsigned int> image_sum_a, const PtrStep_<unsigned long long> image_sqsum_a,
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DevMem2Df result)
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{
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const int x = blockIdx.x * blockDim.x + threadIdx.x;
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const int y = blockIdx.y * blockDim.y + threadIdx.y;
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if (x < result.cols && y < result.rows)
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{
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float image_sum_r_ = (float)(
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(image_sum_r.ptr(y + h)[x + w] - image_sum_r.ptr(y)[x + w]) -
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(image_sum_r.ptr(y + h)[x] - image_sum_r.ptr(y)[x]));
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float image_sqsum_r_ = (float)(
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(image_sqsum_r.ptr(y + h)[x + w] - image_sqsum_r.ptr(y)[x + w]) -
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(image_sqsum_r.ptr(y + h)[x] - image_sqsum_r.ptr(y)[x]));
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float image_sum_g_ = (float)(
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(image_sum_g.ptr(y + h)[x + w] - image_sum_g.ptr(y)[x + w]) -
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(image_sum_g.ptr(y + h)[x] - image_sum_g.ptr(y)[x]));
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float image_sqsum_g_ = (float)(
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(image_sqsum_g.ptr(y + h)[x + w] - image_sqsum_g.ptr(y)[x + w]) -
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(image_sqsum_g.ptr(y + h)[x] - image_sqsum_g.ptr(y)[x]));
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float image_sum_b_ = (float)(
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(image_sum_b.ptr(y + h)[x + w] - image_sum_b.ptr(y)[x + w]) -
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(image_sum_b.ptr(y + h)[x] - image_sum_b.ptr(y)[x]));
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float image_sqsum_b_ = (float)(
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(image_sqsum_b.ptr(y + h)[x + w] - image_sqsum_b.ptr(y)[x + w]) -
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(image_sqsum_b.ptr(y + h)[x] - image_sqsum_b.ptr(y)[x]));
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float image_sum_a_ = (float)(
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(image_sum_a.ptr(y + h)[x + w] - image_sum_a.ptr(y)[x + w]) -
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(image_sum_a.ptr(y + h)[x] - image_sum_a.ptr(y)[x]));
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float image_sqsum_a_ = (float)(
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(image_sqsum_a.ptr(y + h)[x + w] - image_sqsum_a.ptr(y)[x + w]) -
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(image_sqsum_a.ptr(y + h)[x] - image_sqsum_a.ptr(y)[x]));
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float ccorr = result.ptr(y)[x];
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float rdenom = rsqrtf(templ_sqsum_scale * (image_sqsum_r_ - weight * image_sum_r_ * image_sum_r_
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+ image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_
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+ image_sqsum_b_ - weight * image_sum_b_ * image_sum_b_
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+ image_sqsum_a_ - weight * image_sum_a_ * image_sum_a_));
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result.ptr(y)[x] = min(1.f, (ccorr - image_sum_r_ * templ_sum_scale_r
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- image_sum_g_ * templ_sum_scale_g
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- image_sum_b_ * templ_sum_scale_b
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- image_sum_a_ * templ_sum_scale_a) * rdenom);
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}
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}
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void matchTemplatePrepared_CCOFF_NORMED_8UC4(
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int w, int h,
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const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
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const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
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const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
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const DevMem2D_<unsigned int> image_sum_a, const DevMem2D_<unsigned long long> image_sqsum_a,
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unsigned int templ_sum_r, unsigned int templ_sqsum_r,
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unsigned int templ_sum_g, unsigned int templ_sqsum_g,
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unsigned int templ_sum_b, unsigned int templ_sqsum_b,
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unsigned int templ_sum_a, unsigned int templ_sqsum_a,
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DevMem2Df result)
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{
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dim3 threads(32, 8);
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dim3 grid(divUp(result.cols, threads.x), divUp(result.rows, threads.y));
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float weight = 1.f / (w * h);
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float templ_sum_scale_r = templ_sum_r * weight;
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float templ_sum_scale_g = templ_sum_g * weight;
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float templ_sum_scale_b = templ_sum_b * weight;
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float templ_sum_scale_a = templ_sum_a * weight;
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float templ_sqsum_scale = templ_sqsum_r - weight * templ_sum_r * templ_sum_r
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+ templ_sqsum_g - weight * templ_sum_g * templ_sum_g
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+ templ_sqsum_b - weight * templ_sum_b * templ_sum_b
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+ templ_sqsum_a - weight * templ_sum_a * templ_sum_a;
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matchTemplatePreparedKernel_CCOFF_NORMED_8UC4<<<grid, threads>>>(
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w, h, weight,
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templ_sum_scale_r, templ_sum_scale_g, templ_sum_scale_b, templ_sum_scale_a,
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templ_sqsum_scale,
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image_sum_r, image_sqsum_r,
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image_sum_g, image_sqsum_g,
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image_sum_b, image_sqsum_b,
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image_sum_a, image_sqsum_a,
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result);
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cudaSafeCall(cudaThreadSynchronize());
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}
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template <int cn>
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__global__ void normalizeKernel_8U(
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int w, int h, const PtrStep_<unsigned long long> image_sqsum,
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